Category Archives: wildlife management

On an Experimental Design Mafia for Ecology

Ecologist A does an experiment and publishes Conclusions G and H. Ecologist B reads this paper and concludes that A’s data support Conclusions M and N and do not support Conclusions G and H. Ecologist B writes to Journal X editor to complain and is told to go get stuffed because Journal X never makes a mistake with so many members of the Editorial Board who have Nobel Prizes. This is an inviting fantasy and I want to examine one possible way to avoid at least some of these confrontations without having to fire all the Nobel Prize winners on the Editorial Board.

We go back to the simple question: Can we agree on what types of data are needed for testing this hypothesis? We now require our graduate students or at least our Nobel colleagues to submit the experimental design for their study to the newly founded Experimental Design Mafia for Ecology (or in French DEME) who will provide a critique of the formulation of the hypotheses to be tested and the actual data that will be collected. The recommendations of the DEME will be nonbinding, and professors and research supervisors will be able to ignore them with no consequences except that the coveted DEME icon will not be able to be published on the front page of the resulting papers.

The easiest part of this review will be the data methods, and this review by the DEME committee will cover the current standards for measuring temperature, doing aerial surveys for elephants, live-trapping small mammals, measuring DBH on trees, determining quadrat size for plant surveys, and other necessary data collection problems. This advice alone should hypothetically remove about 25% of future published papers that use obsolete models or inadequate methods to measure or count ecological items.

The critical part of the review will be the experimental design part of the proposed study. Experimental design is important even if it is designated as undemocratic poppycock by your research committee. First, the DEME committee will require a clear statement of the hypothesis to be tested and the alternative hypotheses. Words which are used too loosely in many ecological works must be defended as having a clear operational meaning, so that idea statements that include ‘stability’ or ‘ecosystem integrity’ may be questioned and their meaning sharpened. Hypotheses that forbid something from occurring or allow only type Y events to occur are to be preferred, and for guidance applicants may be referred to Popper (1963), Platt (1964), Anderson (2008) or Krebs (2019). If there is no alternative hypothesis, your research plan is finished. If you are using statistical methods to test your hypotheses, read Ioannidis (2019).

Once you have done all this, you are ready to go to work. Do not be concerned if your research plan goes off target or you get strange results. Be prepared to give up hypotheses that do not fit the observed facts. That means you are doing creative science.

The DEME committee will have to be refreshed every 5 years or so such that fresh ideas can be recognized. But the principles of doing good science are unlikely to change – good operational definitions, a set of hypotheses with clear predictions, a writing style that does not try to cover up contrary findings, and a forward look to what next? And the ecological world will slowly become a better place with fewer sterile arguments about angels on the head of a pin.

Anderson, D.R. (2008) ‘Model Based Inference in the Life Sciences: A Primer on Evidence.‘ (Springer: New York.) ISBN: 978-0-387-74073-7.

Ioannidis, J.P.A. (2019). What have we (not) learnt from millions of scientific papers with P values? American Statistician 73, 20-25. doi: 10.1080/00031305.2018.1447512.

Krebs, C.J. (2020). How to ask meaningful ecological questions. In Population Ecology in Practice. (Eds D.L. Murray and B.K. Sandercock.) Chapter 1, pp. 3-16. Wiley-Blackwell: Amsterdam. ISBN: 978-0-470-67414-7

Platt, J. R. (1964). Strong inference. Science 146, 347-353. doi: 10.1126/science.146.3642.347.

Popper, K. R. (1963) ‘Conjectures and Refutations: The Growth of Scientific Knowledge.’ (Routledge and Kegan Paul: London.). ISBN: 9780415285940

On the Use of Statistics in Ecological Research

There is an ever-deepening cascade of statistical methods and if you are going to be up to date you will have to use and cite some of them in your research reports or thesis. But before you jump into these methods, you might consider a few tidbits of advice. I suggest three rules and a few simple guidelines:

Rule 1. For descriptive papers keep to descriptive statistics. Every good basic statistics book has advice on when to use means to describe “average values”, when to use medians, or percentiles. Follow their advice and do not in your report generate any hypotheses except in the discussion. And follow the simple advice of statisticians not to generate and then test a hypothesis with the same set of data. Descriptive papers are most valuable. They can lead us to speculations and suggest hypotheses and explanations, but they do not lead us to strong inference.

Rule 2. For explanatory papers, the statistical rules become more complicated. For scientific explanation you need 2 or more alternative hypotheses that make different, non-overlapping predictions. The predictions must involve biological or physical mechanisms. Correlations alone are not mechanisms. They may help to lead you to a mechanism, but the key is that the mechanism must involve a cause and an effect. A correlation of a decline in whale numbers with a decline in sunspot numbers may be interesting but only if you can tie this correlation into an actual mechanism that affects birth or death rates of the whales.

Rule 3. For experimental papers you have access to a large variety of books and papers on experimental design. You must have a control or unmanipulated group, or for a comparative experiment a group A with treatment X, and a group B with treatment Y. There are many rules in the writings of experimental design that give good guidance (e.g. Anderson 2008; Eberhardt 2003; Johnson 2002; Shadish et al. 2002; Underwood 1990).

For all these ecology papers, consider the best of the recent statistical admonitions. Use statistics to enlighten not to obfuscate the reader. Use graphics to illustrate major results. Avoid p-values (Anderson et al. 2000; Ioannidis 2019a, 2019b). Measure effect sizes for different treatments (Nakagawa and Cuthill 2007). Add to these general admonitions the conventional rules of paper or report submission – do not argue with the editor, argue a small amount with the reviewers (none are perfect), and put your main messages in the abstract. And remember that it is possible there was some interesting research done before the year 2000.

Anderson, D.R. (2008) ‘Model Based Inference in the Life Sciences: A Primer on Evidence.’ (Springer: New York.). 184 pp.

Anderson, D.R., Burnham, K.P., and Thompson, W.L. (2000). Null hypothesis testing: problems, prevalence, and an alternative. Journal of Wildlife Management 64, 912-923.

Eberhardt, L.L. (2003). What should we do about hypothesis testing? Journal of Wildlife Management 67, 241-247.

Ioannidis, J.P.A. (2019a). Options for publishing research without any P-values. European Heart Journal 40, 2555-2556. doi: 10.1093/eurheartj/ehz556.

Ioannidis, J. P. A. (2019b). What have we (not) learnt from millions of scientific papers with P values? American Statistician 73, 20-25. doi: 10.1080/00031305.2018.1447512.

Johnson, D.H. (2002). The importance of replication in wildlife research. Journal of Wildlife Management 66, 919-932.

Nakagawa, S. and Cuthill, I.C. (2007). Effect size, confidence interval and statistical significance: a practical guide for biologists. Biological Reviews 82, 591-605. doi: 10.1111/j.1469-185X.2007.00027.x.

Shadish, W.R, Cook, T.D., and Campbell, D.T. (2002) ‘Experimental and Quasi-Experimental Designs for Generalized Causal Inference.’ (Houghton Mifflin Company: New York.)

Underwood, A. J. (1990). Experiments in ecology and management: Their logics, functions and interpretations. Australian Journal of Ecology 15, 365-389.

On Three Kinds of Ecology Papers

There are many possible types of papers that discuss ecology, and in particular I want to deal only with empirical studies that deal with terrestrial and aquatic populations, communities, or ecosystems. I will not discuss here theoretical studies or modelling studies. I suggest it is possible to classify papers in ecological science journals that deal with field studies into three categories which I will call Descriptive Ecology, Explanatory Ecology, and Experimental Ecology. Papers in all these categories deal with a description of some aspects of the ecological world and how it works but they differ in their scientific impact.

Descriptive Ecology publications are essential to ecological science because they present some details of the natural history of an ecological population or community that is vital to our growing understanding of the biota of the Earth. There is much literature in this group, and ecologists all have piles of books on the local natural history of birds, moths, turtles, and large mammals, to mention only a few. Fauna and flora compilations pull much of this information together to guide beginning students and the interested public in increased knowledge of local fauna and flora. These publications are extremely valuable because they form the natural history basis of our science, and greatly outnumber the other two categories of papers. The importance of this information has been a continuous message of ecologists over many years (e.g. Bartholomew 1986; Dayton 2003; Travis 2020).

The scientific journals that professional ecologists read are mostly concerned with papers that can be classified as Explanatory Ecology and Experimental Ecology. In a broad sense these two categories can be described as providing a good story to tie together and thus explain the known facts of natural history or alternatively to define a set of hypotheses that provide alternative explanations for these facts and then to test these hypotheses experimentally. Rigorous ecology like all good science proceeds from the explanatory phase to the experimental phase. Good natural history provides several possible explanations for ecological events but does not stop there. If a particular bird population is declining, we need first to make a guess from natural history if this decline might be from disease, habitat loss, or predation. But to proceed to successful management of this conservation problem, we need studies that distinguish the cause(s) of our ecological problems, as recognized by Caughley (1994) and emphasized by Hone et al. (2018). Consequently the flow in all the sciences is from descriptive studies to explanatory ideas to experimental validation. Without experimental validation ‘ecological ideas’ can transform into ‘ecological opinions’ to the detriment of our science. This is not a new view of scientific method (Popper 1963) but it does need to be repeated (Betini et al. 2017). 

If I repeat this too much, I suggest you do a survey of how often ecological papers in your favorite journal are published without ever using the word ‘hypothesis’ or ‘experiment’. A historical survey of these or similar words would be a worthwhile endeavour for an honours or M.Sc. student in any one of the ecological subdisciplines. The favourite explanation offered in many current papers is climate change, a particularly difficult hypothesis to test because, if it is specified vaguely enough, it is impossible to test experimentally. Telling interesting stories should not be confused with rigorous experimental ecology.

Bartholomew, G. A. (1986). The role of natural history in comtemporary biology. BioScience 36, 324-329. doi: 10.2307/1310237

Betini, G.S., Avgar, T., and Fryxell, John M. (2017). Why are we not evaluating multiple competing hypotheses in ecology and evolution? Royal Society Open Science 4, 160756. doi: 10.1098/rsos.160756.

Caughley, G. (1994). Directions in conservation biology. Journal of Animal Ecology 63, 215-244. doi: 10.2307/5542

Dayton, P.K. (2003). The importance of the natural sciences to conservation. American Naturalist 162, 1-13. doi: 10.1086/376572

Hone, J., Drake, Alistair, and Krebs, C.J. (2018). Evaluating wildlife management by using principles of applied ecology: case studies and implications. Wildlife Research 45, 436-445. doi: 10.1071/WR18006.

Popper, K. R. (1963) ‘Conjectures and Refutations: The Growth of Scientific Knowledge.’ (Routledge and Kegan Paul: London.)

Travis, Joseph (2020). Where is natural history in ecological, evolutionary, and behavioral science? American Naturalist 196, 1-8. doi: 10.1086/708765.

On Declining Bird Populations

The conservation literature and the media are alive with cries of declining bird populations around the world (Rosenberg et al. 2019). Birds are well liked by people, and an important part of our environment so they garner a lot of attention when the cry goes out that all is not well. The problems from a scientific perspective is what evidence is required to “cry wolf’. There are many different opinions on what data provide reliable evidence. There is a splendid critique of the Rosenberg et al paper by Brian McGill that you should read::
https://dynamicecology.wordpress.com/2019/09/20/did-north-america-really-lose-3-billion-birds-what-does-it-mean/

My object here is to add a comment from the viewpoint of population ecology. It might be useful for bird ecologists to have a brief overview of what ecological evidence is required to decide that a bird population or a bird species or a whole group of birds is threatened or endangered. One simple way to make this decision is with a verbal flow chart and I offer here one example of how to proceed.

  1. Get accurate and precise data on the populations of interest. If you claim a population is declining or endangered, you need to define the population and know its abundance over a reasonable time period.

Note that this is already a nearly impossible demand. For birds that are continuously resident it is possible to census them well. Let me guess that continuous residency occurs in at most 5% or fewer of the birds of the world. The other birds we would like to protect are global or local migrants or move unpredictably in search of food resources, so it is difficult to define a population and determine if the population as a whole is rising or falling. Compounding all this are the truly rare bird species that are difficult to census like all rare species. Dorey and Walker (2018) examine these concerns for Canada.

The next problem is what is a reasonable time period for the census data. The Committee on the Status of Endangered Wildlife in Canada (COSEWIC) gives 10 years or 3 generations, whichever is longer (see web link below). So now we need to know the generation time of the species of concern. We can make a guess at generation time but let us stick with 10 years for the moment. For how many bird species in Canada do we have 10 years of accurate population estimates?

  • Next, we need to determine the causes of the decline if we wish to instigate management actions. Populations decline because of a falling reproductive rate, increasing death rate, or higher emigration rates. There are very few birds for which we have 10 years of diagnosis for the causes of changes in these vital rates. Strong conclusions should not rest on weak data.

The absence of much of these required data force conservation biologists to guess about what is driving numbers down, knowing only that population numbers are falling. Typically, many things are happening over the 10 years of assessment – climate is changing, habitats are being lost or gained, invasive species are spreading, new toxic chemical are being used for pest control, diseases are appearing, the list is long. We have little time or money to determine the critical limiting factors. We can only make a guess.

  • At this stage we must specify an action plan to recommend management actions for the recovery of the declining bird population. Management actions are limited. We cannot in the short term alter climate. Regulating toxic chemical use in agriculture takes years. In a few cases we can set aside more habitat as a generalized solution for all declining birds. We have difficulty controlling invasive species, and some invasive species might be native species expanding their geographic range (e.g. Bodine and Capaldi 2017, Thibault et al. 2018).

Conservation ecologists are now up against the wall because all management actions that are recommended will cost money and will face potential opposition from some people. Success is not guaranteed because most of the data available are inadequate. Medical doctors face the same problem with rare diseases and uncertain treatments when deciding how to treat patients with no certainty of success.

In my opinion the data on which the present concern over bird losses is too poor to justify the hyper-publicity about declining birds. I realize most conservation biologists will disagree but that is why I think we need to lift our game by having a more rigorous set of data rules for categories of concern in conservation. A more balanced tone of concern may be more useful in gathering public support for management efforts. Stanton et al. (2018) provide a good example for farmland birds. Overuse of the word ‘extinction’ is counterproductive in my opinion. Trying to provide better data is highly desirable so that conservation papers do not always end with the statement ‘but detailed mechanistic studies are lacking’. Pleas for declining populations ought to be balanced by recommendations for solutions to the problem. Local solutions are most useful, global solutions are critical in the long run but given current global governance are too much fairy tales.

Bodine, E.N. and Capaldi, A. (2017). Can culling Barred Owls save a declining Northern Spotted Owl population? Natural Resource Modeling 30, e12131. doi: 10.1111/nrm.12131.

Dorey, K. and Walker, T.R. (2018). Limitations of threatened species lists in Canada: A federal and provincial perspective. Biological Conservation 217, 259-268. doi: 10.1016/j.biocon.2017.11.018.

Rosenberg, K.V., et al. (2019). Decline of the North American avifauna. Science 366, 120-124. doi: 10.1126/science.aaw1313.

Stanton, R.L., Morrissey, C.A., and Clark, R.G. (2018). Analysis of trends and agricultural drivers of farmland bird declines in North America: A review. Agriculture, Ecosystems & Environment 254, 244-254. doi: 10.1016/j.agee.2017.11.028.

Thibault, M., et al. (2018). The invasive Red-vented bulbul (Pycnonotus cafer) outcompetes native birds in a tropical biodiversity hotspot. PLoS ONE 13, e0192249. doi: 10.1371/journal.pone.0192249.

http://cosewic.ca/index.php/en-ca/assessment-process/wildlife-species-assessment-process-categories-guidelines/quantitative-criteria

On Fires in Australia

The fires of Australia in their summer 2019-20 are in the news constantly, partly because the media survive on death and destruction and partly because to date we have never seen a whole continent burn up. It is hardly a ‘Welcome to the Anthropocene”  kind of event to celebrate, and the northern media display the fires as nearly all news of the Southern Hemisphere is treated, something unusual, often bad, but of no general importance to the real world of the Northern Hemisphere.

What do we hear from a cacophony of public opinion?

“Nothing unusual. We have always had fires in the past. Why in 1863…..”
“Nothing to do with climate change. Climate has always been changing….(see point 1)
“Main cause had been Green Policies. If we had more forestry, there would have been many fewer trees to burn….”
“Inadequate controlled burning because of the Greens’ policies….(see point 3)
“Why doesn’t the Government do something about this?”
“Fortunately these fires are a rare event and not likely to occur again…….

In reply an ecologist might offer these facts:

  1. Much research by plant geographers and ecologists have shown how many plant communities are dominated by fire. The boreal forest is one, the chaparral of Southern California is another, the grasslands of Africa and the Great Plains of the USA are yet more.
  2. By preventing fire in these communities over time the fuel load builds up so that, should there be a subsequent fire, the fire severity would be very high.
  3. By building houses, towns, and cities in these plant communities fire danger increases, and an active plan of fire management must be implemented. Most of these plans are effective for normal fires but for extreme conditions no fire management plan is effective.
  4. Climate change is now producing extreme conditions that were once very rare but are now commonly achieved. With no rainfall, high winds, and temperatures over 40-45ºC fires cannot be contained. Severe fires generate their own weather that accelerates fire spread with embers being blown kilometers ahead of the active fire front.
  5. The long-term plan to have controlled patch burns to relieve these fire conditions are impossible to implement because they require no wind, low temperatures, and considerable person-power to prevent controlled burns getting away from containment lines should the weather change.

Since a sizeable fraction of dangerous fires are deliberately set by humans, methods to detect and prevent this behaviour could help in some cases. Infrastructure such as power lines could be upgraded to reduce the likelihood of falling power poles and lines shorting out. All this will cost money, and the less the fire frequency, the fewer the people willing to pay more taxes to reduce public risk. Some serious thinking is needed now because Australia 2020 is just the start of a century of fire, drought, floods, and high winds. We do not need the politicians of 2050 telling us “why didn’t someone warn us?

There is a very large literature on fire in human landscapes (e.g. Gibbons et al. 2012), and I include only a few references here. They illustrate that the landscape effects of fire are multiple and area specific. Much more field research is needed, and landscape ecology has a vital role to play in understanding and managing the interface of humans and fire.

Badia, A. et al. (2019). Wildfires in the wildland-urban interface in Catalonia: Vulnerability analysis based on land use and land cover change. Science of The Total Environment 673, 184-196. doi: 10.1016/j.scitotenv.2019.04.012.

Gibbons, P, et. al. (2012) Land management practices associated with house loss in wildfires. PLoS ONE 7(1): e29212. https://doi.org/10.1371/journal.pone.0029212

Gustafsson, L. et al. (2019). Rapid ecological response and intensified knowledge accumulation following a north European mega-fire. Scandinavian Journal of Forest Research 34, 234-253. doi: 10.1080/02827581.2019.1603323.

Minor, J. and Boyce, G.A. (2018). Smokey Bear and the pyropolitics of United States forest governance. Political Geography 62, 79-93. doi: 10.1016/j.polgeo.2017.10.005.

Ramage, B.S., O’Hara, K.L., and Caldwell, B.T. (2010). The role of fire in the competitive dynamics of coast redwood forests. Ecosphere 1(6), art20. doi: 10.1890/ES10-00134.1.

Thoughts on Wildlife Management

Stop for a moment and think about where we are now in the science of wildlife management and conservation. Look at the titles of paper in our scientific journals. The vast majority of the problems and questions being investigated are basically about how to reverse some human-caused folly. Many wildlife scientists, ecologists, and organismal biologists entered science with the goal of understanding natural systems from the ecosystem down to the molecular level but in the past 60 years the focus has had to shift. This shift has occurred almost unnoticed because it has been gradual in the time scale of human employment and turnover. The ecosystems of the world are in a frightful mess, and virtually all the mess is human caused. So while we engage in many discussions about how to define the ‘Anthropocene’ in the geological sciences (Correia et al. 2018; Zalasiewicz et al. 2017) ecological science is left in the dust because it never leads to ‘progress’.

This came home to me when I considered which of the many study sites in which classical ecological research has been carried out over the last century still exist. They have been replaced by suburbs, highways, shopping malls, farms, and industrial sites, and the associated waterways have been altered beyond recognition. A simple consequence is that if you wished to repeat a famous ecological study done 50-100 years ago, you could not do it because the site has been obliterated. One consequence is that if we wish to do field work today, we choose a new site that has so far been protected from development.

The elephant in the room now is climate change, so if you choose to investigate the trophic dynamics of an Amazonian forest area (for example), you face two problems – the site could be obliterated by ‘development’ before your work is completed, or the climate changes expected during the next 80 years will alter the trophic dynamics of your site so that your current results are no guide to the future state of these ecosystems. Whither predictive ecology? Many of us thought that by discovering and analyzing ecological principles, we could closely approach the precision of the physical sciences, the laws of physics and chemistry. But the more we search for generality in ecology the less we find. We retreat to general principles that are too vague to be of any predictive use for the wildlife managers of the future.

The thought has been prevalent that by investigating the changes in communities and ecosystems in the past we would have a guide to the future. This belief guides much of paleo-ecological research as well as the projections from evolutionary research of how species have recovered from the recent ice ages. But the past is perhaps not necessarily a good guide to the future when we add in the human footprint arising from the combination of population growth and climate change. Ecologists are left with the concern that our findings have much current value but perhaps little long-term insight. 

Many current papers on ecological changes assume a simple extrapolation predicting the future state of ecosystems (e.g. Martin et al. 2019; Yu et al. 2019). Testing these kinds of extrapolations is virtually possible within the lifetime of the typical ecologist, and my concern is that management actions that are recommended now may be completely off the mark in 30 years. Several papers have warned about this (e.g. Inkpen 2017; La Marca et al. 2019; Mouquet et al. 2015) but as far as I can determine to little effect.

I think the bottom line might be a recommendation for all predictive papers to state a strong prediction and a defined time frame so that there is hope of testing the predictive model in ecological time. Otherwise we ecologists begin to fall into the realm of science fiction.

Correia, R.A. et al. (2018). Pivotal 20th century contributions to the development of the Anthropocene concept: overview and implications. Current Science 115, 1871-1875. doi: 10.18520/cs/v115/i10/1871-1875.

Inkpen, S.A. (2017). Are humans disturbing conditions in ecology? Biology & Philosophy 32, 51-71. doi: 10.1007/s10539-016-9537-z.

La Marca, W. et al. (2019). The influence of data source and species distribution modelling method on spatial conservation priorities. Diversity & Distributions 25, 1060-1073. doi: 10.1111/ddi.12924.

Martin, D. et al. (2019). Long-distance influence of the Rhône River plume on the marine benthic ecosystem: Integrating descriptive ecology and predictive modelling. Science of The Total Environment 673, 790-809. doi: 10.1016/j.scitotenv.2019.04.010.

Mouquet, N. et al. (2015). Predictive ecology in a changing world. Journal of Applied Ecology 52, 1293-1310. doi: 10.1111/1365-2664.12482.

Yu, F., et al. (2019). Climate and land use changes will degrade the distribution of Rhododendrons in China. Science of The Total Environment 659, 515-528. doi: 10.1016/j.scitotenv.2018.12.223.

Zalasiewicz, J. et al. (2017). The Working Group on the Anthropocene: Summary of evidence and interim recommendations. Anthropocene 19, 55-60. doi: 10.1016/j.ancene.2017.09.001.